Many enterprises have built their own digital twin factory model for physical factory planning, simulation optimization, and real-time monitoring. However, the digital twin system (DTS), which has a ...single domain, short time cycle, and unfulfillable services, cannot fully reflect the interaction and integration of the physical and informational world required by smart manufacturing. Therefore, research on the smart factory DTS (SFDTS) construction and application with cross-domain, multiple models have important influence on smart manufacturing. Given the above problems, this paper proposes the concept and composition of a digital twin manufacturing ecosystem (DTME) based on the requirements and characteristics of the product life cycle. It analyzes the construction requirements of the DTME for a factory DTS(FDTS), product DTS(PDTS), and supply chain DTS(SCDTS) from the perspective of the life cycle. Finally, the smart factory DTS architecture is applied to the digital and intelligent upgrading of the hydraulic cylinder factory. The experimental results reveal the intelligent improvement of the hydraulic factory, reduction of work-in-progress inventory, and advance of delivery time, proving the feasibility and effectiveness of the SFDTS.
The increased rate of cyber-attacks on the power system necessitates the need for innovative solutions to ensure its resiliency. This work builds on the advancement in the IoT to provide a practical ...framework that is able to respond to multiple attacks on a network of interconnected microgrids. This paper provides an IoT-based digital twin (DT) of the cyber-physical system that interacts with the control system to ensure its proper operation. The IoT cloud provision of the energy cyber-physical and the DT are mathematically formulated. Unlike other cybersecurity frameworks in the literature, the proposed one can mitigate an individual as well as coordinated attacks. The framework is tested on a distributed control system and the security measures are implemented using cloud computing. The physical controllers are implemented using single-board computers. The practical results show that the proposed DT is able to mitigate the coordinated false data injection and the denial of service cyber-attacks.
Smart manufacturing is the core idea of the fourth industrial evolution. For a smart manufacturing shop floor, real-time monitoring, simulation and prediction of manufacturing operations are vital to ...improve the production efficiency and flexibility. In this paper, the Cyber-Physical System (CPS) and Digital Twin technologies are introduced to build the interconnection and interoperability of a physical shop floor and corresponding cybershop floor. A Digital Twin-based Cyber-Physical Production System (DT-CPPS) is further established, and the configuring mechanism, operating mechanism and real-time data-driven operations control of DT-CPPS are discussed in detail. It is expected that DT-CPPS will provide the basis for shop floors to march towards smart manufacturing.
Process evaluation is widely accepted as an effective strategy to improve product quality and shorten its development cycle. However, there has been very little research on how to evaluate the ...process plan with the dynamic change of the machining condition and uncertain available manufacturing resources. This paper proposes a novel process evaluation method based on digital twin technology. Three core technologies embodied in the proposed method are illustrated in details: 1) real-time mapping mechanism between the collected data in machining and the process design information; 2) construction of the digital twin-based machining process evaluation (DT-MPPE) framework; and 3) process evaluation driven by digital twin data. To elaborate on how to apply the proposed method to the reality, we present a detailed implementation process of the proposed DT-MPPE method for the key parts of the marine diesel engine. Meanwhile, the future work to completely fulfill digital twin-based smart process planning for complex products is discussed.
•An easy-to-deploy and simple-to-use framework for digital-twin-based cyber-physical production system (CPPS) is proposed.•The configuration and runtime of digital-twin-based CPPS is realized based ...on digital twin modeling, dynamic resource registration, and event-driven distributed cooperation.•A prototype is implemented and verified in our lab environment.
The rapid development new generation of information technologies facilitate the emergence of cyber-physical production system (CPPS) which could pave a way to exploring new smart manufacturing solutions. Digital twin (DT) is the technical core for establishing CPPS in the context of industry 4.0. Developing an easy-to-deploy and simple-to-use DT-based CPPS is a critical research gap. In this paper, a systemic framework is proposed to provide guidelines for rapid system configuration and easy runtime of DT-based CPPS by integrating CPS, DT modeling technologies, event-driven distributed cooperation mechanisms, and web technologies. The concept of CPS node (CPSN) for manufacturing resources is established by integrating semantic information model, 3D geometric model and function modules. Various CPSNs are orchestrated as an autonomous CPPS using dynamic resource registration and binding technologies. To achieve easy runtime of DT-based CPPS, event-driven distributed cooperation among CPSNs and web-based remote control of CPPS are proposed respectively. Finally, to verify the feasibility of the proposed framework, a prototype of DT-based CPPS is implemented, based on which an exemplary case is conducted.
•A digital twin-driven intelligent gear health management method is developed to assess the gear surface degradation progression.•A high-fidelity digital twin model is built for the gear transmission ...system.•A transfer learning algorithm is proposed for gear wear severity assessment.•Two endurance tests are conducted to validate the effectiveness of the proposed methodology.
Gearbox has a compact structure, a stable transmission capability, and a high transmission efficiency. Thus, it is widely applied as a power transmission system in various applications, such as wind turbines, industrial machinery, aircraft, space vehicles, and land vehicles. The gearbox usually operates in harsh and non-stationary working environments, expediting the degradation process of the gear surface. The degradation process may lead to severe gear failures, such as tooth breakage and root crack, which could damage the gear transmission system. Therefore, it is essential to assess the progression of gear surface degradation in order to ensure a reliable operation. The digital twin is an emerging technology for machine health management. A high-fidelity digital twin model can help reflect the operation status of the gearbox and reveal the corresponding degradation mechanism, which could benefit the remaining useful life (RUL) prediction and the predictive maintenance-based decision-making framework. This paper develops a digital twin-driven intelligent health management method to monitor and assess the gear surface degradation progression. The developed method can effectively reveal the gear wear propagation characteristics and predict the RUL accurately. Furthermore, the knowledge learned from digital twin models can be well transferred to the surface wear assessment of the physical gearbox in wide industrial applications, which is of great practical significance. Two endurance tests with different dominant degradation mechanisms were conducted to validate the effectiveness of the proposed methodology for gear wear assessment.
Under a mass individualisation paradigm, the individualised design of manufacturing systems is difficult as it involves adaptive integrating both new and legacy machines for the formation of part ...families with uncertainty. A systematic virtual model mirroring the real world of manufacturing system is essential to bridge the gap between its design and operation. This paper presents a digital twin-driven methodology for rapid individualised designing of the automated flow-shop manufacturing system. The digital twin merges physics-based system modelling and distributed semi-physical simulation to provide engineering solution analysis capabilities and generates an authoritative digital design of the system at pre-production phase. An effective feedbacking of collected decision-support information from the intelligent multi-objective optimisation of the dynamic execution is presented to boost the applicability of the digital twin vision in the designing of AFMS. Finally, a bi-level iterative coordination mechanism is proposed to achieve optimal design performance for required functions of AFMS. A case study is conducted to prove the feasibility and effectiveness of the proposed methodology.
The signal-processing and intelligent diagnostic and monitoring methods based on motor current signature analysis (MCSA) for induction motors (IM) usually depend on preset parameters. Moreover, many ...of them have difficulty in achieving ideal health monitoring effect with strong noise interference and switching working conditions. To overcome these limitations, a novel digital twin architecture called the Ramanujan digital twin (RDT) is composed. This architecture uses the Ramanujan periodic transform (RPT) as its computational core to detect the potential fault signatures in each monitoring frame. The quantity of interest from IM will be selected and calibrated based on the Bayesian-updated driven calibration mechanism to construct the phenomenal simulation signals with high fidelity to the potential fault signatures. These signals will provide guidance information. The effectiveness and robustness of the RDT are validated through experimental cases.
Over the last few decades, our digitally expanding world has experienced another significant digitalization boost because of the COVID-19 pandemic. Digital transformations are changing every aspect ...of this world. New technological innovations are springing up continuously, attracting increasing attention and investments. Digital twin, one of the highest trending technologies of recent years, is now joining forces with the healthcare sector, which has been under the spotlight since the outbreak of COVID-19. This paper sets out to promote a better understanding of digital twin technology, clarify some common misconceptions, and review the current trajectory of digital twin applications in healthcare. Furthermore, the functionalities of the digital twin in different life stages are summarized in the context of a digital twin model in healthcare. Following the Internet of Things as a service concept and digital twining as a service model supporting Industry 4.0, we propose a paradigm of digital twinning everything as a healthcare service, and different groups of physical entities are also clarified for clear reference of digital twin architecture in healthcare. This research discusses the value of digital twin technology in healthcare, as well as current challenges and insights for future research.
Applications of Digital Twin technology have been growing at an exponential rate, and it is transforming the way businesses operate. In the past few years, Digital Twins leveraged vital business ...applications, and it is predicted that the technology will expand to more applications, use cases, and industries. The purpose of this paper is to do a literature review and explore how Digital Twins streamline intelligent automation in different industries. This paper defines the concept, highlights the evolution and development of Digital Twins, reviews its key enabling technologies, examines its trends and challenges, and explores its applications in different industries.
•Digital Twins have moved from idea to reality much faster in recent years.•The technology is poised to deliver upon its many promises in many industries.•The benefits of creating a Digital Twin solution are too vast and still not fully explored.•Digital Twins will combine with more technologies, such as augmented reality (AR) and AI for better connections, insights, and analytics.
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